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Trust. The successful candidate will work closely with the PI and a PhD student within a larger cross-disciplinary team to construct a quantitative computational model of carbonate biomineralisation
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suited to candidates with strong quantitative and analytical skills and a PhD (or near completion) in cancer epidemiology or a related field. Applicants should have experience in applying or developing
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must either have a PhD in a relevant biological subject or have submitted or about to submit their PhD thesis. Candidates must also have demonstrable expertise in biochemistry, cell biology and/or
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, adapting existing and developing new research methodologies, as well as contributing to ideas for new research projects. You will hold (or be close to completion of) a PhD/DPhil in a Social Science
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-approved systems. Ensure adherence to data security and compliance protocols. Preferred Qualifications MSc or PhD in Bioinformatics, Computational Biology, Computer Science, or a related field. Strong
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literature review and qualitative methods. Ability to work underpresure. Excellent time management skills. A PhD in the field related to the study is preferred Before applying, please note that to work
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-motivated in advancing science. Their active involvement in this project will contribute to their career development, such as increasing their competitiveness in PhD scholarship applications. The successful
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directly with the PI on applying interdisciplinary neuroscience and electrophysiology techniques toward studying the nervous system of the heart. Qualifications: Education 5 years or less from a PhD or MD
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(e.g., survey development, administration, troubleshooting), Excel, and statistical software (e.g., SPSS, R) • Bilingual or conversational in Spanish. All offers of employment are contingent upon
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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD